From 1e45d506c7296d2077bd3fc9ca52611a4d3d027b Mon Sep 17 00:00:00 2001
From: camenduru <54370274+camenduru@users.noreply.github.com>
Date: Fri, 13 Oct 2023 22:55:10 +0300
Subject: [PATCH] test

---
 LLaVA_13b_8bit_colab.ipynb | 37 ++++++++++++++++++++++++++++---------
 1 file changed, 28 insertions(+), 9 deletions(-)

diff --git a/LLaVA_13b_8bit_colab.ipynb b/LLaVA_13b_8bit_colab.ipynb
index 847d180..7d01b41 100644
--- a/LLaVA_13b_8bit_colab.ipynb
+++ b/LLaVA_13b_8bit_colab.ipynb
@@ -73,6 +73,34 @@
         "!python3 -m llava.serve.gradio_web_server --controller http://localhost:10000 --model-list-mode reload --share"
       ]
     },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "from transformers import AutoTokenizer\n",
+        "from llava.model import LlavaLlamaForCausalLM\n",
+        "import torch\n",
+        "\n",
+        "model_path = \"4bit/llava-v1.5-13b-4GB-8bit\"\n",
+        "tokenizer = AutoTokenizer.from_pretrained(model_path, use_fast=False)\n",
+        "model = LlavaLlamaForCausalLM.from_pretrained(model_path)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "vision_tower = model.get_vision_tower()\n",
+        "if not vision_tower.is_loaded:\n",
+        "    vision_tower.load_model()\n",
+        "vision_tower.to(device='cpu')\n",
+        "image_processor = vision_tower.image_processor"
+      ]
+    },
     {
       "cell_type": "code",
       "execution_count": null,
@@ -89,15 +117,6 @@
         "#     load_4bit=False\n",
         "# )\n",
         "\n",
-        "from transformers import AutoTokenizer\n",
-        "from llava.model import LlavaLlamaForCausalLM\n",
-        "import torch\n",
-        "\n",
-        "model_path = \"4bit/llava-v1.5-13b-4GB-8bit\"\n",
-        "tokenizer = AutoTokenizer.from_pretrained(model_path, use_fast=False)\n",
-        "model = LlavaLlamaForCausalLM.from_pretrained(model_path)\n",
-        "# model = LlavaLlamaForCausalLM.from_pretrained(model_path, low_cpu_mem_usage=True, load_in_8bit=True, device_map=\"auto\")\n",
-        "\n",
         "vision_tower = model.get_vision_tower()\n",
         "if not vision_tower.is_loaded:\n",
         "    vision_tower.load_model()\n",